The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

Zinc sulfide (ZnS) thin films were deposited on glass substrates using pulsed laser deposition technique. The laser used is the Q-switched Nd: YAG laser with 1064nm wavelength and 1Hz pulse repetition rate and varying laser energy 700mJ-1000mJ with 25 pulse. The substrate temperature was kept constant at 100°C. The structural, morphological and optical properties of ZnS thin films were characterized with X-ray diffraction (XRD), scanning electron microscopy (SEM), atomic force microscope (AFM) and UV-VIS spectrophotometer.

Experimental tests were conducted to investigate the thermal performance (cooling effect) of water mist system consisting of 5μm volume median diameter droplets in reducing the heat gain entering a room through the roof and the west wall by reducing the outside surface temperature due to the evaporative cooling effect during the hot dry summer of Baghdad/Iraq. The test period
was Fifty one days during the months May, June, and July 2012. The single test day consists of 16 test hours starting from 8:00 am to 12:00 pm. The results showed a reduction range of 1.71 to 15.5℃ of the roof outside surface temperature and 21.3 to 76.6% reduction in the daily heat flux entering the room through the roof compared with the case of not using w

The aim of this study is to calculate the ene expenditure from fatty substance contents of the
frog. Rana ridibunda during its hibernation. It was found that, almost, all frogs enter
hibernation during the last week of December and emerge from hibernation during the first
week of March. Hence, January and February are considered the hibernation period.
December is the pre-hibernation period and March is the post-hibernation period. The
reduction in percent of body lipid during the hibernation period was 4.8% in males and 7.7%
in females. The reduction in percent of lipid of fat bodies during the hibernation period was
2.758% in males and 0.733% in females.
The calorific value of R. ridibunda lipid amounted to 1233

Anaerobic digestion is a technology widely used for treatment of organic waste for biogas production as a source for clean energy. In this study, poultry house wastes (PHW) material was examined as a source for biogas production. The effects of inoculum addition, pretreatment of the substrate, and temperature on the biogas production were taken into full consideration. Results revealed that the effect of inoculum addition was more significant than the alkaline pretreatment of raw waste materials. The biogas recovery from inoculated waste materials exceeds its production from wastes without inoculation by approximately 70% at mesophilic conditions. Whereby, the increase of biogas recovery from pretreated wastes was by 20% higher than its